R: Minimum distance estimation in an imprecise probability model
imprProbEst-package
R Documentation
Minimum distance estimation in an imprecise probability model
Description
A minimum distance estimator is calculated for an imprecise probability model.
The imprecise probability model consists of upper coherent previsions whose credal sets are given
by a finite number of constraints on the expectations. The parameter set is finite. The estimator chooses
that parameter such that the empirical measure lies next to the corresponding credal set with respect to
the total variation norm.
Details
Package:
imprProbEst
Type:
Package
Version:
1.0
Date:
2008-10-23
License:
LGPL-3
LazyLoad:
yes
library(imprProbEst
Note
R programming support was given by Matthias Kohl
Author(s)
Robert Hable
Maintainer: Robert Hable <Robert.Hable@uni-bayreuth.de>
References
Hable (2008) Data-Based Decisions under Complex Uncertainty, Ph.D. thesis,
LMU Munich, in preparation
Walley, P. (1991) Statistical reasoning with imprecise probabilities.
Chapman & Hall, London.